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INFO MANAGEMENT L1
INTRODUCTION OF DATABASE SYSTEMS
| Answer | Question |
|---|---|
| Database | an ORGANIZED COLLECTION of structured information, or data |
| Database System (DBS) | an ENTIRE ENVIRONMENT used to manage and maintain the data. |
| Database | The ACTUAL collection of data. |
| Database Management System (DBMS) | The software that provides the PROVIDES INTERFACE between the users/applications and the database. It handles data storage, retrieval, and security. |
| Database Users and Applications: | The people and programs that interact with the system. |
| SQL Category | MySQL SQL Server Oracle PostgreSQL |
| No SQL Category | MongoDB CouchDB |
| Data (INPUT) | is the raw, unprocessed facts, figures, and symbols. It has no meaning on its own outside of its Context. |
| Information (OUTPUT) | is processed, organized, structured, or presented data that makes it meaningful and useful. It answers questions and aids decision-making |
| Database systems | valuable assets for decision-making because they transform raw data into accessible, high-quality information. |
| Data Storage & Retrieval | To store large volumes of data and make it easy to find and retrieve information quickly and efficiently |
| Data Management | To provide tools for creating, updating, and deleting data, and for performing various other manipulations. |
| CRUD | create / can be: insert data/database read / can be: for example, copy update / can be: change or add data delete / can be: remove |
| Data Organization | To structure data in a logical way (like relational tables) to reflect real-world relationships and prevent inconsistencies |
| Data Security | To protect sensitive data from unauthorized access and maintain confidentiality through access controls and other safeguards. |
| Data Integrity & Consistency | ensure data is accurate, consistent, and complete by enforcing rules and constraints, reducing redundancy |
| Fixed structure | determine na agad ‘yong values or data in SQL based |
| Flexible structure | NoSQL-based |
| Backup & Recovery | provide mechanisms for backing up data or restoring it in case of hardware failure or data loss |
| Improved Decision-Making | providing access to organized and reliable data, databases, helps users query, report, and analyze information to make informed decisions |
| Increased Productivity | Automating data management tasks frees up employees from manual work, allowing them to focus on higher-value activities |
| Data Sharing | Facilitate the SHARING of data among multiple users and departments simultaneously, which improves accuracy and timelines |
| Scalability | designed to scale up increasing volumes of data and user demands w/o significant performance degradation |
| Support for Applications | Database are crucial for various applications (can support data, fit for system to handle) from personal contact list to complex enterprise-level systems for financial transactions and inventory management. |
| Data for AI and Analytics | essential for modern applications like data mining and machine learning which rely on vast amounts of high quality data |
| DATABASE ARCHITECTURE | It is the blueprint for a database system, outlining how data is stored, managed, and accessed to support applications and users. |
| DATABASE ARCHITECTURE | It includes components like the data model, the database management system (DBMS), and the schema, and can be organized in different tiers, such as one, two, or three-tier models. |
| Data Model | Defines the logical structure and relationships of the data (e.g., Relational, Hierarchical, NoSQL). |
| Database Management System (DBMS) | The software that controls all access to the Database. |
| Schemas | describes the structure of the database at different levels (Internal, Conceptual, External) |
| Hardware and Software | These form the physical environment the DBMS operates. For a component list, sometimes this is collectively referred to as the DBMS Environment or Storage Subsystem. |
| Internal Schema (Physical Level) | Describes how data is physically stored on storage devices |
| Conceptual Schema (Logical Level) | Describes the logical structure of the entire database. |
| External Schema (View Level) | Describes how data is viewed by different users or applications. |
| One-tier architecture: | The user, application, and database are all on the same machine. This is common for simple applications, but can have limitations in performance and scalability |
| Two-tier architecture: | The client-server model, where a client application communicates directly with the database server. |
| Three-tier architecture: | A more complex model that adds an application server between the client and the database. This provides a presentation tier (client), a business/application tier, and a data tier, improving scalability, security, and flexibility. |
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